TY - GEN
T1 - Distributed Trajectory Generation for Multi-Quadrotors Using Receding Horizon Control and Sequential Convex Programming
AU - Xu, Guangtong
AU - Long, Teng
AU - Wang, Shengyin
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - This paper presents a distributed trajectory planning method supporting parallel computation based on receding horizon control (RHC) and sequential convex programming (SCP) for quadrotor swarms in known environments with obstacles. The proposed method, denoted as distributed RHC-SCP (dRHC-SCP), divides the swarm trajectory planning problem into a series of short-horizon planning problems to reduce the computation burden. In each planning horizon, dRHC-SCP solves the swarm trajectory planning problem in an iterative framework via efficient SCP algorithm. In the iterative process of SCP, dRHC-SCP uses the trajectories generated in the last iteration as the nominal trajectories for next iteration to achieve distributed planning and decoupling of the inter-quadrotor collision avoidance constraints. Simulation studies on several scenarios verify the efficiency merit of dRHC-SCP. Comparative results with decoupled SCP (dSCP) demonstrate that dRHC-SCP has higher computational efficiency and better scalability for quadrotor swarm trajectory planning.
AB - This paper presents a distributed trajectory planning method supporting parallel computation based on receding horizon control (RHC) and sequential convex programming (SCP) for quadrotor swarms in known environments with obstacles. The proposed method, denoted as distributed RHC-SCP (dRHC-SCP), divides the swarm trajectory planning problem into a series of short-horizon planning problems to reduce the computation burden. In each planning horizon, dRHC-SCP solves the swarm trajectory planning problem in an iterative framework via efficient SCP algorithm. In the iterative process of SCP, dRHC-SCP uses the trajectories generated in the last iteration as the nominal trajectories for next iteration to achieve distributed planning and decoupling of the inter-quadrotor collision avoidance constraints. Simulation studies on several scenarios verify the efficiency merit of dRHC-SCP. Comparative results with decoupled SCP (dSCP) demonstrate that dRHC-SCP has higher computational efficiency and better scalability for quadrotor swarm trajectory planning.
UR - http://www.scopus.com/inward/record.url?scp=85080891384&partnerID=8YFLogxK
U2 - 10.1109/ICUS48101.2019.8996027
DO - 10.1109/ICUS48101.2019.8996027
M3 - Conference contribution
AN - SCOPUS:85080891384
T3 - Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019
SP - 837
EP - 841
BT - Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Conference on Unmanned Systems, ICUS 2019
Y2 - 17 October 2019 through 19 October 2019
ER -